1k citations · 3.8k across the 69 of their papers we have counts for
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Detection, Instance Segmentation, and Classification for Astronomical Surveys with Deep Learning (DeepDISC): Detectron2 Implementation and Demonstration with Hyper Suprime-Cam Data
G. M. Merz, Y. Liu, C. J. Burke +4
The next generation of wide-field deep astronomical surveys will deliver unprecedented amounts of images through the 2020s and beyond. As both the sensitivity and depth of observat…
The Dark Energy Survey Data Release 2
DES Collaboration, T. M. C. Abbott, M. Adamow +132
We present the second public data release of the Dark Energy Survey, DES DR2, based on optical/near-infrared imaging by the Dark Energy Camera mounted on the 4-m Blanco telescope a…
Survey2Survey: A deep learning generative model approach for cross-survey image mapping
Brandon Buncher, Awshesh Nath Sharma, Matias Carrasco Kind
During the last decade, there has been an explosive growth in survey data and deep learning techniques, both of which have enabled great advances for astronomy. The amount of data…
Noise from Undetected Sources in Dark Energy Survey Images
K. Eckert, G. M. Bernstein, A. Amara +66
For ground-based optical imaging with current CCD technology, the Poisson fluctuations in source and sky background photon arrivals dominate the noise budget and are readily estima…
Deep Learning for Multi-Messenger Astrophysics: A Gateway for Discovery in the Big Data Era
Gabrielle Allen, Igor Andreoni, Etienne Bachelet +45
This report provides an overview of recent work that harnesses the Big Data Revolution and Large Scale Computing to address grand computational challenges in Multi-Messenger Astrop…
First Cosmology Results Using Type Ia Supernovae From the Dark Energy Survey: Photometric Pipeline and Light Curve Data Release
D. Brout, M. Sako, D. Scolnic +89
We present griz light curves of 251 Type Ia Supernovae (SNe Ia) from the first 3 years of the Dark Energy Survey Supernova Program's (DES-SN) spectroscopically classified sample. T…